Juan S. Santillana

Working on a matched-architecture pair of Spanish security small models (VectraYX-600M at 661.6M parameters and VectraYX-1B at 1,109M, sharing decoder, tokenizer and special-token layout), the work documents a keyword-harness false positive: the two score almost identically on the lenient B4 tool-use metric (0.660 vs. 0.650), yet a verbatim-reproduction check shows the 600M emits valid tool calls with generalized arguments on 6/6 training examples while the 1B does so on 0/4–6 at every pre-remediation checkpoint; a first-token probe localizes the failure to a missing prior of roughly 10^-4–10^-5 on <|tool_call|>, and a targeted SFT recipe (diverse corpus, 5x learning rate, 2,202 steps, about 3.3 GPU-hours) raises the 1B's valid emission from 0.100 to 0.959 and passes 0.

Working on a matched-architecture pair of Spanish security small models (VectraYX-600M at 661.6M parameters and VectraYX-1B at 1,109M, sharing decoder, tokenizer and special-token layout), the work documents a keyword-harness false positive: the two score almost identically on the lenient B4 tool-use metric (0.660 vs. 0.650), yet a verbatim-reproduction check shows the 600M emits valid tool calls with generalized arguments on 6/6 training examples while the 1B does so on 0/4–6 at every pre-remediation checkpoint; a first-token probe localizes the failure to a missing prior of roughly 10^-4–10^-5 on <|tool_call|>, and a targeted SFT recipe (diverse corpus, 5x learning rate, 2,202 steps, about 3.3 GPU-hours) raises the 1B's valid emission from 0.100 to 0.959 and passes 0.